Overview

Dataset statistics

Number of variables10
Number of observations24
Missing cells26
Missing cells (%)10.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory86.5 B

Variable types

Text6
Categorical2
Numeric1
DateTime1

Dataset

Description대구광역시 수성구_평생학습마을 현황_20210623
Author대구광역시 수성구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15084044&dataSetDetailId=150840441ee94bd26af2c&provdMethod=FILE

Alerts

설립연도 is highly overall correlated with 상태High correlation
상태 is highly overall correlated with 설립연도High correlation
단체명 has 7 (29.2%) missing valuesMissing
장소 has 5 (20.8%) missing valuesMissing
등록일 has 14 (58.3%) missing valuesMissing
고유번호 has unique valuesUnique
마을이름 has unique valuesUnique
주소 has unique valuesUnique
강좌프로그램 has unique valuesUnique

Reproduction

Analysis started2024-04-19 05:37:38.219677
Analysis finished2024-04-19 05:37:39.124566
Duration0.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고유번호
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-04-19T14:37:39.241718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length9
Mean length6.5
Min length1

Characters and Unicode

Total characters156
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row2
2nd row3
3rd row4
4th row5
5th row11
ValueCountFrequency (%)
2 1
 
4.2%
3 1
 
4.2%
ins_000000000240 1
 
4.2%
ins_000000000180 1
 
4.2%
ins_000000000156 1
 
4.2%
ins_000000000154 1
 
4.2%
ins_000000000182 1
 
4.2%
25 1
 
4.2%
ins_000000000153 1
 
4.2%
23 1
 
4.2%
Other values (14) 14
58.3%
2024-04-19T14:37:39.541689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 76
48.7%
1 15
 
9.6%
2 11
 
7.1%
5 9
 
5.8%
I 8
 
5.1%
N 8
 
5.1%
S 8
 
5.1%
_ 8
 
5.1%
3 4
 
2.6%
4 4
 
2.6%
Other values (4) 5
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 124
79.5%
Uppercase Letter 24
 
15.4%
Connector Punctuation 8
 
5.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 76
61.3%
1 15
 
12.1%
2 11
 
8.9%
5 9
 
7.3%
3 4
 
3.2%
4 4
 
3.2%
8 2
 
1.6%
7 1
 
0.8%
9 1
 
0.8%
6 1
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
I 8
33.3%
N 8
33.3%
S 8
33.3%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 132
84.6%
Latin 24
 
15.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 76
57.6%
1 15
 
11.4%
2 11
 
8.3%
5 9
 
6.8%
_ 8
 
6.1%
3 4
 
3.0%
4 4
 
3.0%
8 2
 
1.5%
7 1
 
0.8%
9 1
 
0.8%
Latin
ValueCountFrequency (%)
I 8
33.3%
N 8
33.3%
S 8
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 156
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 76
48.7%
1 15
 
9.6%
2 11
 
7.1%
5 9
 
5.8%
I 8
 
5.1%
N 8
 
5.1%
S 8
 
5.1%
_ 8
 
5.1%
3 4
 
2.6%
4 4
 
2.6%
Other values (4) 5
 
3.2%

마을이름
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-04-19T14:37:39.776575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length8.5416667
Min length4

Characters and Unicode

Total characters205
Distinct characters89
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row코오롱단지 평생학습마을
2nd row수성행복마을
3rd rowe편한세상 한마음 평생학습마을
4th row황금희망마을
5th row수성동일하이빌 평생학습마을
ValueCountFrequency (%)
평생학습마을 5
 
14.7%
코오롱단지 1
 
2.9%
아너스사랑마을 1
 
2.9%
황금미소마을 1
 
2.9%
만촌느지마을 1
 
2.9%
지산녹색마을 1
 
2.9%
중동평생학습마을센터 1
 
2.9%
두레마을 1
 
2.9%
만촌달빛평생학습마을 1
 
2.9%
파동청춘평생학습마을 1
 
2.9%
Other values (20) 20
58.8%
2024-04-19T14:37:40.151208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 24
 
11.7%
을 23
 
11.2%
10
 
4.9%
학 9
 
4.4%
습 9
 
4.4%
평 8
 
3.9%
생 8
 
3.9%
지 5
 
2.4%
동 4
 
2.0%
하 3
 
1.5%
Other values (79) 102
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 194
94.6%
Space Separator 10
 
4.9%
Lowercase Letter 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 24
 
12.4%
을 23
 
11.9%
학 9
 
4.6%
습 9
 
4.6%
평 8
 
4.1%
생 8
 
4.1%
지 5
 
2.6%
동 4
 
2.1%
하 3
 
1.5%
랑 3
 
1.5%
Other values (77) 98
50.5%
Space Separator
ValueCountFrequency (%)
10
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 194
94.6%
Common 10
 
4.9%
Latin 1
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 24
 
12.4%
을 23
 
11.9%
학 9
 
4.6%
습 9
 
4.6%
평 8
 
4.1%
생 8
 
4.1%
지 5
 
2.6%
동 4
 
2.1%
하 3
 
1.5%
랑 3
 
1.5%
Other values (77) 98
50.5%
Common
ValueCountFrequency (%)
10
100.0%
Latin
ValueCountFrequency (%)
e 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 194
94.6%
ASCII 11
 
5.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 24
 
12.4%
을 23
 
11.9%
학 9
 
4.6%
습 9
 
4.6%
평 8
 
4.1%
생 8
 
4.1%
지 5
 
2.6%
동 4
 
2.1%
하 3
 
1.5%
랑 3
 
1.5%
Other values (77) 98
50.5%
ASCII
ValueCountFrequency (%)
10
90.9%
e 1
 
9.1%

동
Categorical

Distinct11
Distinct (%)45.8%
Missing0
Missing (%)0.0%
Memory size324.0 B
만촌동
5 
황금동
4 
수성동
3 
파동
3 
상동
2 
Other values (6)
7 

Length

Max length4
Median length3
Mean length2.8333333
Min length2

Unique

Unique5 ?
Unique (%)20.8%

Sample

1st row수성동
2nd row수성동
3rd row만촌동
4th row황금동
5th row상동

Common Values

ValueCountFrequency (%)
만촌동 5
20.8%
황금동 4
16.7%
수성동 3
12.5%
파동 3
12.5%
상동 2
 
8.3%
지산동 2
 
8.3%
고산1동 1
 
4.2%
두산동 1
 
4.2%
범물동 1
 
4.2%
고산3동 1
 
4.2%

Length

2024-04-19T14:37:40.313165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
만촌동 5
20.8%
황금동 4
16.7%
수성동 3
12.5%
파동 3
12.5%
상동 2
 
8.3%
지산동 2
 
8.3%
고산1동 1
 
4.2%
두산동 1
 
4.2%
범물동 1
 
4.2%
고산3동 1
 
4.2%

주소
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-04-19T14:37:40.511079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length20
Mean length17.666667
Min length3

Characters and Unicode

Total characters424
Distinct characters89
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row(수성동4가) (수성동4가) (수성동4가) 수성롯데캐슬, 우방사랑마을, 수성우방팔레스 () (수성동4가)
2nd row(수성4가동) (수성4가동) 16통,17통,19통 ()
3rd row(만촌3동) (만촌3동) (만촌3동) (만촌3동) 수성e편한세상 2차 () () (만촌3동)
4th row(황금2동) 15통,16통,17통
5th row수성동일하이빌레이크시티
ValueCountFrequency (%)
만촌3동 6
 
10.3%
수성동4가 5
 
8.6%
4
 
6.9%
수성4가동 2
 
3.4%
황금2동 2
 
3.4%
만촌1동 2
 
3.4%
지산1동 2
 
3.4%
3통,4통,5통,7통,8통 1
 
1.7%
범물2동 1
 
1.7%
21통 1
 
1.7%
Other values (32) 32
55.2%
2024-04-19T14:37:40.862273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35
 
8.3%
통 34
 
8.0%
( 30
 
7.1%
) 30
 
7.1%
동 26
 
6.1%
1 25
 
5.9%
, 24
 
5.7%
성 15
 
3.5%
수 14
 
3.3%
2 12
 
2.8%
Other values (79) 179
42.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 226
53.3%
Decimal Number 78
 
18.4%
Space Separator 35
 
8.3%
Open Punctuation 30
 
7.1%
Close Punctuation 30
 
7.1%
Other Punctuation 24
 
5.7%
Lowercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
통 34
 
15.0%
동 26
 
11.5%
성 15
 
6.6%
수 14
 
6.2%
촌 10
 
4.4%
만 10
 
4.4%
가 7
 
3.1%
지 5
 
2.2%
운 4
 
1.8%
타 4
 
1.8%
Other values (64) 97
42.9%
Decimal Number
ValueCountFrequency (%)
1 25
32.1%
2 12
15.4%
4 11
14.1%
3 11
14.1%
5 4
 
5.1%
8 4
 
5.1%
6 4
 
5.1%
9 3
 
3.8%
7 3
 
3.8%
0 1
 
1.3%
Space Separator
ValueCountFrequency (%)
35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 226
53.3%
Common 197
46.5%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
통 34
 
15.0%
동 26
 
11.5%
성 15
 
6.6%
수 14
 
6.2%
촌 10
 
4.4%
만 10
 
4.4%
가 7
 
3.1%
지 5
 
2.2%
운 4
 
1.8%
타 4
 
1.8%
Other values (64) 97
42.9%
Common
ValueCountFrequency (%)
35
17.8%
( 30
15.2%
) 30
15.2%
1 25
12.7%
, 24
12.2%
2 12
 
6.1%
4 11
 
5.6%
3 11
 
5.6%
5 4
 
2.0%
8 4
 
2.0%
Other values (4) 11
 
5.6%
Latin
ValueCountFrequency (%)
e 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 226
53.3%
ASCII 198
46.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35
17.7%
( 30
15.2%
) 30
15.2%
1 25
12.6%
, 24
12.1%
2 12
 
6.1%
4 11
 
5.6%
3 11
 
5.6%
5 4
 
2.0%
8 4
 
2.0%
Other values (5) 12
 
6.1%
Hangul
ValueCountFrequency (%)
통 34
 
15.0%
동 26
 
11.5%
성 15
 
6.6%
수 14
 
6.2%
촌 10
 
4.4%
만 10
 
4.4%
가 7
 
3.1%
지 5
 
2.2%
운 4
 
1.8%
타 4
 
1.8%
Other values (64) 97
42.9%

설립연도
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)29.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2016.0417
Minimum2012
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-04-19T14:37:40.986409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile2012
Q12013
median2017
Q32018
95-th percentile2019
Maximum2020
Range8
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.5956346
Coefficient of variation (CV)0.0012874905
Kurtosis-1.321016
Mean2016.0417
Median Absolute Deviation (MAD)2
Skewness-0.35902497
Sum48385
Variance6.7373188
MonotonicityNot monotonic
2024-04-19T14:37:41.096903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2017 5
20.8%
2018 5
20.8%
2013 4
16.7%
2012 3
12.5%
2015 3
12.5%
2019 3
12.5%
2020 1
 
4.2%
ValueCountFrequency (%)
2012 3
12.5%
2013 4
16.7%
2015 3
12.5%
2017 5
20.8%
2018 5
20.8%
2019 3
12.5%
2020 1
 
4.2%
ValueCountFrequency (%)
2020 1
 
4.2%
2019 3
12.5%
2018 5
20.8%
2017 5
20.8%
2015 3
12.5%
2013 4
16.7%
2012 3
12.5%

단체명
Text

MISSING 

Distinct17
Distinct (%)100.0%
Missing7
Missing (%)29.2%
Memory size324.0 B
2024-04-19T14:37:41.261247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length15.176471
Min length10

Characters and Unicode

Total characters258
Distinct characters75
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)100.0%

Sample

1st row코오롱단지평생학습마을 추진위원회
2nd row수성행복마을 추진위원회
3rd rowe편한세상 한마음 평생학습마을 추진위원회
4th row황금희망마을 추진위원회
5th row수성동일하이빌 평생학습마을 추진위원회
ValueCountFrequency (%)
추진위원회 17
40.5%
평생학습마을 5
 
11.9%
코오롱단지평생학습마을 1
 
2.4%
화정마을 1
 
2.4%
수성행복마을 1
 
2.4%
두레마을 1
 
2.4%
파동청춘평생학습마을 1
 
2.4%
하나타운학습마을 1
 
2.4%
범물드림마을 1
 
2.4%
메트로팔레스5단지 1
 
2.4%
Other values (12) 12
28.6%
2024-04-19T14:37:41.543214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25
 
9.7%
마 18
 
7.0%
위 17
 
6.6%
회 17
 
6.6%
을 17
 
6.6%
원 17
 
6.6%
추 17
 
6.6%
진 17
 
6.6%
학 8
 
3.1%
습 8
 
3.1%
Other values (65) 97
37.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 231
89.5%
Space Separator 25
 
9.7%
Decimal Number 1
 
0.4%
Lowercase Letter 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 18
 
7.8%
위 17
 
7.4%
회 17
 
7.4%
을 17
 
7.4%
원 17
 
7.4%
추 17
 
7.4%
진 17
 
7.4%
학 8
 
3.5%
습 8
 
3.5%
평 7
 
3.0%
Other values (62) 88
38.1%
Space Separator
ValueCountFrequency (%)
25
100.0%
Decimal Number
ValueCountFrequency (%)
5 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 231
89.5%
Common 26
 
10.1%
Latin 1
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 18
 
7.8%
위 17
 
7.4%
회 17
 
7.4%
을 17
 
7.4%
원 17
 
7.4%
추 17
 
7.4%
진 17
 
7.4%
학 8
 
3.5%
습 8
 
3.5%
평 7
 
3.0%
Other values (62) 88
38.1%
Common
ValueCountFrequency (%)
25
96.2%
5 1
 
3.8%
Latin
ValueCountFrequency (%)
e 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 231
89.5%
ASCII 27
 
10.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25
92.6%
5 1
 
3.7%
e 1
 
3.7%
Hangul
ValueCountFrequency (%)
마 18
 
7.8%
위 17
 
7.4%
회 17
 
7.4%
을 17
 
7.4%
원 17
 
7.4%
추 17
 
7.4%
진 17
 
7.4%
학 8
 
3.5%
습 8
 
3.5%
평 7
 
3.0%
Other values (62) 88
38.1%

장소
Text

MISSING 

Distinct17
Distinct (%)89.5%
Missing5
Missing (%)20.8%
Memory size324.0 B
2024-04-19T14:37:41.727009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length14
Mean length10.210526
Min length4

Characters and Unicode

Total characters194
Distinct characters84
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)78.9%

Sample

1st row황금2동 행정복지센터 2층 등
2nd row아파트 내 교육장
3rd row아파트 내 교육장
4th row아파트 내 주민까페 등
5th row아파트 내 경로당
ValueCountFrequency (%)
아파트 8
15.7%
내 8
15.7%
등 5
 
9.8%
경로당 3
 
5.9%
2층 2
 
3.9%
행정복지센터 2
 
3.9%
황금2동 2
 
3.9%
교육장 2
 
3.9%
주민까페 1
 
2.0%
585번지 1
 
2.0%
Other values (17) 17
33.3%
2024-04-19T14:37:42.048936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32
 
16.5%
파 10
 
5.2%
아 9
 
4.6%
트 8
 
4.1%
내 8
 
4.1%
로 6
 
3.1%
당 6
 
3.1%
지 5
 
2.6%
경 5
 
2.6%
2 5
 
2.6%
Other values (74) 100
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 149
76.8%
Space Separator 32
 
16.5%
Decimal Number 11
 
5.7%
Open Punctuation 1
 
0.5%
Close Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 10
 
6.7%
아 9
 
6.0%
트 8
 
5.4%
내 8
 
5.4%
로 6
 
4.0%
당 6
 
4.0%
지 5
 
3.4%
경 5
 
3.4%
등 5
 
3.4%
동 4
 
2.7%
Other values (66) 83
55.7%
Decimal Number
ValueCountFrequency (%)
2 5
45.5%
5 3
27.3%
6 1
 
9.1%
8 1
 
9.1%
1 1
 
9.1%
Space Separator
ValueCountFrequency (%)
32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 149
76.8%
Common 45
 
23.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 10
 
6.7%
아 9
 
6.0%
트 8
 
5.4%
내 8
 
5.4%
로 6
 
4.0%
당 6
 
4.0%
지 5
 
3.4%
경 5
 
3.4%
등 5
 
3.4%
동 4
 
2.7%
Other values (66) 83
55.7%
Common
ValueCountFrequency (%)
32
71.1%
2 5
 
11.1%
5 3
 
6.7%
( 1
 
2.2%
6 1
 
2.2%
) 1
 
2.2%
8 1
 
2.2%
1 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 149
76.8%
ASCII 45
 
23.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32
71.1%
2 5
 
11.1%
5 3
 
6.7%
( 1
 
2.2%
6 1
 
2.2%
) 1
 
2.2%
8 1
 
2.2%
1 1
 
2.2%
Hangul
ValueCountFrequency (%)
파 10
 
6.7%
아 9
 
6.0%
트 8
 
5.4%
내 8
 
5.4%
로 6
 
4.0%
당 6
 
4.0%
지 5
 
3.4%
경 5
 
3.4%
등 5
 
3.4%
동 4
 
2.7%
Other values (66) 83
55.7%

강좌프로그램
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-04-19T14:37:42.257596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length20
Mean length16.125
Min length4

Characters and Unicode

Total characters387
Distinct characters138
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row웃음치료교실, 탁구, 요가, 천연화장품 등
2nd row실버건강체조, 웃음치료, 민요교실
3rd row탁구, 예쁜글씨, 오카리나, 메이크업
4th row생활체조, 폐백음식만들기, 천연염색
5th row노래교실, 요리교실, 단전호흡, 댄스, 요가
ValueCountFrequency (%)
요가 8
 
10.5%
등 4
 
5.3%
탁구 4
 
5.3%
노래교실 3
 
3.9%
만들기 2
 
2.6%
건강체조 2
 
2.6%
웃음치료 2
 
2.6%
요리교실 2
 
2.6%
생활체조 2
 
2.6%
웃음치료교실 1
 
1.3%
Other values (46) 46
60.5%
2024-04-19T14:37:42.617942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
52
 
13.4%
, 43
 
11.1%
요 13
 
3.4%
실 11
 
2.8%
교 10
 
2.6%
가 9
 
2.3%
기 7
 
1.8%
체 7
 
1.8%
스 7
 
1.8%
조 6
 
1.6%
Other values (128) 222
57.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 285
73.6%
Space Separator 52
 
13.4%
Other Punctuation 45
 
11.6%
Lowercase Letter 3
 
0.8%
Uppercase Letter 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
요 13
 
4.6%
실 11
 
3.9%
교 10
 
3.5%
가 9
 
3.2%
기 7
 
2.5%
체 7
 
2.5%
스 7
 
2.5%
조 6
 
2.1%
생 6
 
2.1%
구 6
 
2.1%
Other values (119) 203
71.2%
Other Punctuation
ValueCountFrequency (%)
, 43
95.6%
; 1
 
2.2%
& 1
 
2.2%
Lowercase Letter
ValueCountFrequency (%)
p 1
33.3%
m 1
33.3%
a 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
M 1
50.0%
E 1
50.0%
Space Separator
ValueCountFrequency (%)
52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 285
73.6%
Common 97
 
25.1%
Latin 5
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
요 13
 
4.6%
실 11
 
3.9%
교 10
 
3.5%
가 9
 
3.2%
기 7
 
2.5%
체 7
 
2.5%
스 7
 
2.5%
조 6
 
2.1%
생 6
 
2.1%
구 6
 
2.1%
Other values (119) 203
71.2%
Latin
ValueCountFrequency (%)
M 1
20.0%
E 1
20.0%
p 1
20.0%
m 1
20.0%
a 1
20.0%
Common
ValueCountFrequency (%)
52
53.6%
, 43
44.3%
; 1
 
1.0%
& 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 285
73.6%
ASCII 102
 
26.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
52
51.0%
, 43
42.2%
M 1
 
1.0%
E 1
 
1.0%
; 1
 
1.0%
p 1
 
1.0%
m 1
 
1.0%
a 1
 
1.0%
& 1
 
1.0%
Hangul
ValueCountFrequency (%)
요 13
 
4.6%
실 11
 
3.9%
교 10
 
3.5%
가 9
 
3.2%
기 7
 
2.5%
체 7
 
2.5%
스 7
 
2.5%
조 6
 
2.1%
생 6
 
2.1%
구 6
 
2.1%
Other values (119) 203
71.2%

등록일
Date

MISSING 

Distinct7
Distinct (%)70.0%
Missing14
Missing (%)58.3%
Memory size324.0 B
Minimum2013-12-23 00:00:00
Maximum2020-12-31 00:00:00
2024-04-19T14:37:42.742547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:37:42.840856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

상태
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
활성
21 
비활성
3 

Length

Max length3
Median length2
Mean length2.125
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row비활성
2nd row비활성
3rd row비활성
4th row활성
5th row활성

Common Values

ValueCountFrequency (%)
활성 21
87.5%
비활성 3
 
12.5%

Length

2024-04-19T14:37:42.946273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:37:43.052532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
활성 21
87.5%
비활성 3
 
12.5%

Interactions

2024-04-19T14:37:38.682130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-19T14:37:43.119838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고유번호마을이름동주소설립연도단체명장소강좌프로그램등록일상태
고유번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
마을이름1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
동1.0001.0001.0001.0000.2441.0000.0001.0000.6410.214
주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
설립연도1.0001.0000.2441.0001.0001.0000.9451.0001.000NaN
단체명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
장소1.0001.0000.0001.0000.9451.0001.0001.0001.000NaN
강좌프로그램1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
등록일1.0001.0000.6411.0001.0001.0001.0001.0001.000NaN
상태1.0001.0000.2141.000NaN1.000NaN1.000NaN1.000
2024-04-19T14:37:43.257758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동상태
동1.0000.082
상태0.0821.000
2024-04-19T14:37:43.337606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설립연도동상태
설립연도1.0000.1450.879
동0.1451.0000.082
상태0.8790.0821.000

Missing values

2024-04-19T14:37:38.828700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T14:37:38.975241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-04-19T14:37:39.074792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

고유번호마을이름동주소설립연도단체명장소강좌프로그램등록일상태
02코오롱단지 평생학습마을수성동(수성동4가) (수성동4가) (수성동4가) 수성롯데캐슬, 우방사랑마을, 수성우방팔레스 () (수성동4가)2012코오롱단지평생학습마을 추진위원회<NA>웃음치료교실, 탁구, 요가, 천연화장품 등<NA>비활성
13수성행복마을수성동(수성4가동) (수성4가동) 16통,17통,19통 ()2012수성행복마을 추진위원회<NA>실버건강체조, 웃음치료, 민요교실<NA>비활성
24e편한세상 한마음 평생학습마을만촌동(만촌3동) (만촌3동) (만촌3동) (만촌3동) 수성e편한세상 2차 () () (만촌3동)2012e편한세상 한마음 평생학습마을 추진위원회<NA>탁구, 예쁜글씨, 오카리나, 메이크업<NA>비활성
35황금희망마을황금동(황금2동) 15통,16통,17통2013황금희망마을 추진위원회황금2동 행정복지센터 2층 등생활체조, 폐백음식만들기, 천연염색2013-12-23활성
411수성동일하이빌 평생학습마을상동수성동일하이빌레이크시티2013수성동일하이빌 평생학습마을 추진위원회아파트 내 교육장노래교실, 요리교실, 단전호흡, 댄스, 요가<NA>활성
512지산효도마을지산동(지산1동) 10통,11통,12통2013지산효도마을 추진위원회<NA>노래교실, 웃음치료, EM발효강좌2013-12-23활성
613노다지마을수성동(수성동4가) 수성화성쌍용타운2013노다지마을 추진위원회아파트 내 교육장요가, 탁구2013-12-23활성
714꿈꾸는 하늘채 평생학습마을파동수성못 코오롱하늘채2015꿈꾸는 하늘채 평생학습마을 추진위원회아파트 내 주민까페 등요가, 스포츠댄스, 북카페<NA>활성
815희망찬 화정마을고산1동(신매동) 시지삼주한라협화타운2015희망찬 화정마을 추진위원회아파트 내 경로당건강체조, 요가, 서예, 탁구2015-12-15활성
917우방행복마을만촌동(만촌3동) 만촌우방타운1차2017우방행복마을 추진위원회아파트 내 강당민요, 장구2017-02-14활성
고유번호마을이름동주소설립연도단체명장소강좌프로그램등록일상태
1422하나타운학습마을고산3동(매호동) 시지하나타운2018하나타운학습마을 추진위원회아파트 내 경로당실버체조<NA>활성
1523파동청춘평생학습마을파동3통,4통,5통,7통,8통2018파동청춘평생학습마을 추진위원회파동 제1경로당생활체조<NA>활성
16INS_000000000153만촌달빛평생학습마을만촌동(만촌2동)18통2018<NA>만촌달빛커뮤니티센터중국어,영어,하모니카<NA>활성
1725두레마을파동2통,6통2018두레마을 추진위원회두레새마을금고 2층업사이클 패브릭페인팅, 천연한방 생활용품 만들기2018-01-19활성
18INS_000000000182중동평생학습마을센터중동9통2018중동행복마을 추진위원회중동 585번지파크 및 스크린골프<NA>활성
19INS_000000000154지산녹색마을지산동(지산1동) 1통,8통,9통,34통(무학아파트)2017<NA>엔젤허브(수성구 지범로 25길 6) 등녹색체험교실, 친환경교실, 노래교실<NA>활성
20INS_000000000156만촌느지마을만촌동(만촌1동) 1통,2통,5통,14통,18통,36통2019<NA>느지경로당건강체조, 요가 등<NA>활성
21INS_000000000180황금미소마을황금동(황금2동) 11통,13통2019<NA>황금2동 행정복지센터셀프파마배우기 등<NA>활성
22INS_000000000240아너스사랑마을황금동태왕아너스2019<NA>태왕아너스 경로당생활요가, 생활탁구, 바둑<NA>활성
23INS_000000000250상동함장마을상동(상동) 4통2020<NA>공간울림역사연극, 악기놀이, 학부모영어스쿨2020-12-31활성